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The Unseen: A Case Study of Innovative Methods for Investigating Historic Mine Workings

2021· article· en· W3197844732 on OpenAlexaffabout
A Hartzenberg, Adriano de Mendonça Joaquim, Olga Gibbons, Thomas D. Coleman

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsDocumentationClosing (real estate)Closure (psychology)Plan (archaeology)Mining engineeringCivil engineeringEngineeringOpen-pit miningHistoric sitePillarConstruction engineeringEnvironmental planningArchaeologyArchitectural engineeringGeographyComputer sciencePolitical scienceLaw

Abstract

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Abstract Canadian mining operations have long been key contributors to economic vitality. This has resulted in Canada standing at the forefront of implementing best practices that relate to mine closure projects. In the case of closing historic mines this can be a particularly challenging task as often the level of information available is much less than active mines preparing to close. Closing historic mines provides an opportunity to apply new, and innovative methods to collect the data required to design and execute a successful mine closure plan. The site discussed in this study is in northern Canada and used interconnecting open pit and underground mining methods while in operation but has been closed for over half a century. Historic documents indicate that the mine was closed after a failure occurred at depth and some backfill material was lost. A pond currently exists where the open pit was located. This study is Rock Mechanics focused and discusses the methods used to assess the geometry and stability of the historic mine workings. The need for innovation stemmed from the limited historic plans and documentation that existed. Empirical methods suggested that the crown pillar at the site was unstable and should have failed, which did not align with on-site observations. Therefore, an alternative method of assessing the stability was required which involved undertaking bathymetric and three-dimensional sonar surveys to gain a better spatial understanding of the open pit and underground environment. The surveys confirmed that there were no visible signs of instability in the areas where the surveys were done. Advantages and limitations exist for the methods used to complete the survey and use the survey results during this investigation. These will be discussed in this paper.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0110.007
Scholarly communication0.0050.002
Open science0.0040.005
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.267
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2021
Admission routes2
Has abstractyes

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